Journal Article

Using social-network analysis to map institutional actors’ links with vulnerable municipalities under climate change in Honduras’ dry corridor. Pathways towards improved cooperation and territorial interventions

The Honduras dry corridor, located in Central America’s Pacific region, has high natural climatevariability. Nearly half of the Honduran population depends on socio-economic activities linkedto agriculture, making climate-change adaptation crucial for the agricultural sector to ensure foodand nutrition security. This research analyzes how institutional structures function and interact asa network to investigate the spatial coherence and relevance of public- and private-sector in-terventions related to agriculture, climate change, and food security in 153 municipalities ofHonduras’ dry corridor. We employed a Social Network Analysis (SNA) approach to examinethese interactions over the territories, revealing two network patterns: the first favors a singlemunicipality, observed only in the Central District where Honduras’ capital is located; the secondis an egocentric network, favoring a single institution, observed in four cases, particularly inmunicipalities bordering with El Salvador and Guatemala. The SNA results reveal a spatialmisalignment, where only 9% of interventions linked to climate-change adaptation are conductedin the highly vulnerable, outlying zones located farthest from the capital. The study highlights theneed for improved coordination and strategic prioritization of interventions in the most vulner-able municipalities within the Honduras dry corridor, specifically improvement in collaborativeactions, use of resources, and setting strategic priorities in regions where future demand willrequire progressively mobilizing institutional capabilities. By identifying the current gaps andmisalignments in institutional actions, this research provides valuable insights for policymakersand stakeholders to enhance collaborative efforts to ensure that climate-change adaptationmeasures effectively target the most vulnerable areas.